In radio systems, signal detection methods are performed to determine presence of a valid signal at a given frequency of a radio spectrum. Methods that resort to demodulation of the signal are fundamentally limited by the performance of the demodulator. For example, FM demodulator performance is inherently limited by the effects of impulse noise at low signal-to-noise ratios (SNRs). In some cases, correlation techniques can be applied prior to demodulation, however these require that a fixed pattern (known to the receiver) be embedded in the transmitted signal, which is not practical for a broadcast signal. Methods that resort to computing the received signal strength (noise power plus signal power) are fundamentally limited in the sense that they do not distinguish between noise power and signal power and therefore are not very useful for negative SNR values.
For example, post-demodulation methods typically demodulate an incoming RF signal and perform filtering such as bandpass filtering. The resulting filtered signal then has its power integrated over time. Such post-demodulation signal detection is fundamentally limited by the modulator performance. However, a demodulator breaks down at low SNRs due to impulses. Accordingly, large amounts of data are needed. For example, approximately 2 seconds of data are needed to detect the presence of a signal at a SNR of −3 dB, which can be unsuitable for real-time detection in a radio system. Accordingly, post-demodulation methods are generally unsuitable for determining whether a RF signal such as an FM signal is present at a given channel. A need thus exists for improved methods of signal detection, particularly at low or negative SNR levels.